Practical Application of Drive-By Monitoring Technology to Road Roughness Estimation Using Buses in Service

Abstract

The efficiency of vehicles and travel comfort are maintained by the effective management of road pavement conditions. Pavement conditions can be inspected at a low cost by drive-by monitoring technology. Drive-by monitoring technology is a method of collecting data from sensors installed on a running vehicle. This technique enables quick and low-cost inspections. However, most existing technologies assume that the vehicle runs at a constant speed. Therefore, this study devises a theoretical framework that estimates road unevenness without prior information about the vehicle’s mechanical parameters even when the running speed changes. This paper also shows the required function of sensors for this scheme. The required ability is to collect the three-axis acceleration vibration and position data simultaneously. A field experiment was performed to examine the applicability of sensors with both functions to the proposed methods. Each sensor was installed on a bus in service in this field experiment. The vehicle’s natural frequency estimated from the measured data ranges from 1 to 2 Hz, but the natural frequency estimated by the proposed method is 0.71 Hz. However, the estimated road unevenness does not change significantly with changes in the vehicle’s estimated parameters. The results found that the accuracy of road unevenness estimation seems to be acceptable with the conventional method and the new method. Future work will include improving the algorithm and accuracy verification of the schemes.

Study on Multi-Mode Switching Control Strategy of Active Suspension Based on Road Estimation

“…According to the random data of road roughness measured, the value range and mean value of the vertical displacement power spectral density G q ( n ) of different levels of the road surface are obtained by the algorithm. According to the standards of ISO/TC 108/SC2N67 and GB7031 “Vehicle Vibration Input—Road Flatness Representation”, the value range and mean value of vertical displacement power spectral density G q ( n 0 ) of the road at different levels are listed, as shown in Table 1 [ 4 ].…”

“…The vibration signal is collected by the sensor in the process of vehicle driving, and the signal is solved in reverse to perceive the road conditions of vehicle driving. Combined with vehicle driving parameters, the current control mode of the suspension is identified and switched on, and the intelligent control and regulation of the active suspension system are realized with comprehensive consideration of driving conditions [ 3 , 4 , 5 ].…”

Estimating Bridge Natural Frequencies Based on Modal Analysis of Vehicle–Bridge Synchronized Vibration Data

“…On the other hand, the increasing number of satellites has improved the positioning accuracy of Global Navigation Satellite Systems (GNSS). GNSS devices mounted on a vehicle enable the calculation of window functions for VBI analysis [ 26 ]. Despite the improvements in GNSS technology for time synchronization, GNSS device utilization still faces difficulties such as signal blockages and vulnerability to jamming and spoofing activities [ 27 ].…”